code: def test_gradient_ref_lstm(backend_default, gradlstmargs):
      seq_len, input_size, hidden_size, batch_size = gradlstmargs
      NervanaObject.be.bsz = NervanaObject.be.batch_size = batch_size
      gradient_check_ref(seq_len, input_size, hidden_size, batch_size)
  
file_path: neon/tests/test_lstm.py
imports: import itertools
  import numpy
  from neon import NervanaObject, logger
  from neon.initializers.initializer import Constant, Gaussian
  from neon.layers.recurrent import LSTM
  from neon.layers.container import DeltasTree
  from neon.transforms import Logistic, Tanh
  from lstm_ref import LSTM
  from utils import sparse_rand, allclose_with_out
label_desc: Use image node_id 6 for calling a global function with example usage: test_gradient_ref_lstm(backend_default, gradlstmargs) without return types